Engineering Commons^™

A Bibliographic Survey On Detection Of Covid-19 Patients Using Various Sensors In The Field Of Iot, Rutuja Patil, Akshay Sharma, Divya Bhatia, Mugdha Kulkarni, Yashika Patl

Library Philosophy and Practice (e-journal)

Due to a pandemic situation arising from the past few decades and the covid -19 patients are increasing at the rapid rate. Looking in the near future an IOT model is build which can be useful for people in coming years and allows rapid testing and efficient testing methodologies using various sensors such as Temperature, Respiration, RFID etc which takes various parameters. The study focuses around 412 scientific documents such as Journals, articles, book chapters and Patents in various papers. These documents are extracted from the scopus databases after querying with the keywords related to covid patients and IOT. The …

An Efficient Deep-Learning-Based Detection And Classification System For Cyber-Attacks In Iot Communication Networks, Qasem Abu Al-Haija, Saleh Zein-Sabatto

Electrical and Computer Engineering Faculty Research

With the rapid expansion of intelligent resource-constrained devices and high-speed communication technologies, the Internet of Things (IoT) has earned wide recognition as the primary standard for low-power lossy networks (LLNs). Nevertheless, IoT infrastructures are vulnerable to cyber-attacks due to the constraints in computation, storage, and communication capacity of the endpoint devices. From one side, the majority of newly developed cyber-attacks are formed by slightly mutating formerly established cyber-attacks to produce a new attack that tends to be treated as normal traffic through the IoT network. From the other side, the influence of coupling the deep learning techniques with the cybersecurity …

How Live Streaming And Twitch Have Changed The Gaming Industry, Krystal Ruiz

ART 108: Introduction to Games Studies

Live streaming in itself has become a booming industry in which its content consists of “streamers” who live broadcast numerous events and real-time interactions while simultaneously chatting with viewers drawing huge and increasing numbers (Adamovich). Twitch has especially excelled at garnering attention as one of the most popular live streaming platforms that focuses on broadcasting and viewing video game content (Adamovich). Twitch has grown rapidly within the last few years asserting its dominance as one of the major forces in the games industry and becoming a multi-billion-dollar industry (Adamovich). For example, according to Descrier, in 2016 there were approximately 292 …

Conditional Generative Adversarial Network Demosaicing Strategy For Division Of Focal Plane Polarimeters, Garrett Sargent, Bradley M. Ratliff, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Division of focal plane (DoFP), or integrated microgrid polarimeters, typically consist of a 2 × 2 mosaic of linear polarization filters overlaid upon a focal plane array sensor and obtain temporally synchronized polarized intensity measurements across a scene, similar in concept to a Bayer color filter array camera. However, the resulting estimated polarimetric images suffer a loss in resolution and can be plagued by aliasing due to the spatially-modulated microgrid measurement strategy. Demosaicing strategies have been proposed that attempt to minimize these effects, but result in some level of residual artifacts. In this work we propose a conditional generative adversarial …

Survey On Deep Neural Networks In Speech And Vision Systems, M. Alam, Manar D. Samad, Lasitha Vidyaratne, ‪Alexander Glandon, Khan M. Iftekharuddin

Computer Science Faculty Research

This survey presents a review of state-of-the-art deep neural network architectures, algorithms, and systems in speech and vision applications. Recent advances in deep artificial neural network algorithms and architectures have spurred rapid innovation and development of intelligent speech and vision systems. With availability of vast amounts of sensor data and cloud computing for processing and training of deep neural networks, and with increased sophistication in mobile and embedded technology, the next-generation intelligent systems are poised to revolutionize personal and commercial computing. This survey begins by providing background and evolution of some of the most successful deep learning models for intelligent …

A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Prediction methods are important for many applications. In particular, an accurate prediction for the total number of cases for pandemics such as the Covid-19 pandemic could help medical preparedness by providing in time a sufficient supply of testing kits, hospital beds and medical personnel. This thesis experimentally compares the accuracy of ten prediction methods for the cumulative number of Covid-19 pandemic cases. These ten methods include two types of neural networks and extrapolation methods based on best fit linear, best fit quadratic, best fit cubic and Lagrange interpolation, as well as an extrapolation method from Revesz. We also consider the …

Suffix Tree, Minwise Hashing And Streaming Algorithms For Big Data Analysis In Bioinformatics, Sairam Behera

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

In this dissertation, we worked on several algorithmic problems in bioinformatics using mainly three approaches: (a) a streaming model, (b) sux-tree based indexing, and (c) minwise-hashing (minhash) and locality-sensitive hashing (LSH). The streaming models are useful for large data problems where a good approximation needs to be achieved with limited space usage. We developed an approximation algorithm (Kmer-Estimate) using the streaming approach to obtain a better estimation of the frequency of k-mer counts. A k-mer, a subsequence of length k, plays an important role in many bioinformatics analyses such as genome distance estimation. We also developed new methods that use …

Object Recognition And Voice Assistant With Augmented Reality, Juan Estrella

Publications and Research

Our research project aims to provide a visually impaired person with a superimposed map that will guide the individual to the desired destination through a voice controlled virtual assistant application that integrates Augmented Reality (AR) with Artificial Intelligence (AI) Computer Vision and Natural Language Processing (subfields of AI) will be combined to identify the spatial environment and then create a graphic enhancement that provides the most direct route to the specific destination These technologies will be incorporated into the Microsoft Hololens which will be controlled by the user.

Improve The Prototype Of Low-Cost Near-Infrared Diffuse Optical Imaging System, Chen Xu, Mohammed Z. Shakil

Publications and Research

Diffuse Optical Tomography (DOT) and Optical Spectroscopy using near-infrared (NIR) diffused light has demonstrated great potential for the initial diagnosis of tumors and in the assessment of tumor vasculature response to neoadjuvant chemotherapy. The aims of this project are 1) to test the different types of LEDs in the near-infrared range, and design the driving circuit, and test the modulation of LEDs at different frequencies; 2) to test the APDs as a detector, and build the receiver system and compare efficiency with pre-built systems. In this project, we are focusing on creating a low-cost infrared transmission system for tumor and …

Representational Learning Approach For Predicting Developer Expertise Using Eye Movements, Sumeet Maan

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The thesis analyzes an existing eye-tracking dataset collected while software developers were solving bug fixing tasks in an open-source system. The analysis is performed using a representational learning approach namely, Multi-layer Perceptron (MLP). The novel aspect of the analysis is the introduction of a new feature engineering method based on the eye-tracking data. This is then used to predict developer expertise on the data. The dataset used in this thesis is inherently more complex because it is collected in a very dynamic environment i.e., the Eclipse IDE using an eye-tracking plugin, iTrace. Previous work in this area only worked on …

Bibliometric Analysis Of The Literature In The Field Of Information Technology Relatedness, Ilham M, Anis Eliyana, Praptini Yulianti

Library Philosophy and Practice (e-journal)

This bibliometric describe Information Technology Relateness is defined as the use of information technology infrastructure and information technology management processes betweeWas this submission previously published in a journal? Bepress will automatically create an OpenURL for published articles. Learn more about OpenURLsn business units together. There is not much research on Information Technology Relateness by providing a big picture that is visualized from year to year. This study aims to map research in the field of Information Technology Relateness with data from all international research publications. This study performs a bibliometric method and analyzes research data using the Services Analyze …

Deep Reinforcement Learning For Collaborative Edge Computing In Vehicular Networks, Mushu Li, Jie Gao, Lian Zhao, Xuemin Shen

Electrical and Computer Engineering Faculty Research and Publications

Mobile edge computing (MEC) is a promising technology to support mission-critical vehicular applications, such as intelligent path planning and safety applications. In this paper, a collaborative edge computing framework is developed to reduce the computing service latency and improve service reliability for vehicular networks. First, a task partition and scheduling algorithm (TPSA) is proposed to decide the workload allocation and schedule the execution order of the tasks offloaded to the edge servers given a computation offloading strategy. Second, an artificial intelligence (AI) based collaborative computing approach is developed to determine the task offloading, computing, and result delivery policy for vehicles. …

Deep Neural Network For Load Forecasting Centred On Architecture Evolution, Santiago Gomez-Rosero, Miriam A M Capretz, London Hydro

Electrical and Computer Engineering Publications

Nowadays, electricity demand forecasting is critical for electric utility companies. Accurate residential load forecasting plays an essential role as an individual component for integrated areas such as neighborhood load consumption. Short-term load forecasting can help electric utility companies reduce waste because electric power is expensive to store. This paper proposes a novel method to evolve deep neural networks for time series forecasting applied to residential load forecasting. The approach centres its efforts on the neural network architecture during the evolution. Then, the model weights are adjusted using an evolutionary optimization technique to tune the model performance automatically. Experimental results on …

Predicting Residential Energy Consumption Using Wavelet Decomposition With Deep Neural Network, Dagimawi Eneyew, Miriam A M Capretz, Girma Bitsuamlak, London Hydro

Electrical and Computer Engineering Publications

Electricity consumption is accelerating due to economic and population growth. Hence, energy consumption prediction is becoming vital for overall consumption management and infrastructure planning. Recent advances in smart electric meter technology are making high-resolution energy consumption data available. However, many parameters influencing energy consumption are not typically monitored for residential buildings. Therefore, this study’s main objective is to develop a data-driven energy consumption forecasting model (next-hour consumption) for residential houses solely based on analyzing electricity consumption data. This research proposes a deep neural network architecture that combines stationary wavelet transform features and convolutional neural networks. The proposed approach utilizes automatically …

Identifying Depressive Symptoms From Tweets: Figurative Language Enabled Multitask Learning Framework, Shweta Yadav, Jainish Chauhan, Joy Prakash Sain, Krishnaprasad Thirunarayan, Amit P. Sheth, Jeremiah Schumm

Publications

Existing studies on using social media for deriving mental health status of users focus on the depression detection task. However, for case management and referral to psychiatrists, healthcare workers require practical and scalable depressive disorder screening and triage system. This study aims to design and evaluate a decision support system (DSS) to reliably determine the depressive triage level by capturing fine-grained depressive symptoms expressed in user tweets through the emulation of Patient Health Questionnaire-9 (PHQ-9) that is routinely used in clinical practice. The reliable detection of depressive symptoms from tweets is challenging because the 280-character limit on tweets incentivizes the …

Medical Knowledge-Enriched Textual Entailment Framework, Shweta Yadav, Vishal Pallagani, Amit P. Sheth

Publications

One of the cardinal tasks in achieving robust medical question answering systems is textual entailment. The existing approaches make use of an ensemble of pre-trained language models or data augmentation, often to clock higher numbers on the validation metrics. However, two major shortcomings impede higher success in identifying entailment: (1) understanding the focus/intent of the question and (2) ability to utilize the real-world background knowledge to capture the context beyond the sentence. In this paper, we present a novel Medical Knowledge-Enriched Textual Entailment framework that allows the model to acquire a semantic and global representation of the input medical text …

Proportional Voting Based Semi-Unsupervised Machine Learning Intrusion Detection System, Yang G. Kim, Ohbong Kwon, John Yoon

Publications and Research

Feature selection of NSL-KDD data set is usually done by finding co-relationships among features, irrespective of target prediction. We aim to determine the relationship between features and target goals to facilitate different target detection goals regardless of the correlated feature selection. The unbalanced data structure in NSL-KDD data can be relaxed by Proportional Representation (PR). However, adopting PR would deny the notion of winner-take-all by attracting a majority of the vote and also provide a fairly proportional share for any grouping of like-minded data. Furthermore, minorities and majorities would get a fair share of power and representation in data structure …

Software Development With Scrum: A Bibliometric Analysis And Profile, Peter Kokol, Sašo Zagoranski, Marko Kokol

Library Philosophy and Practice (e-journal)

Introduction of the Scrum approach into software engineering has changed the way software is being developed. The Scrum approach emphasizes the active end-user involvement, embracing of change, and /iterative delivery of products. Our study showed that Scrum has different variants or is used in combination with different methods. Some tools not normally used in the conventional software approaches, like gamification, content analysis and grounded theory are also employed. However, Scrum like other software development approach focuses on improvement of software process, software quality, business value, performance, usability and efficiency and at the same time to reduce cost, risk and uncertainty. …

Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

The coronavirus disease 2019 (COVID-19) global pandemic has severely impacted lives across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities similar to viral pneumonia. A Computer-Aided Detection (CAD) system for the detection of COVID-19 using chest radiographs would provide a second opinion for radiologists. For this research, we utilize publicly available datasets that have been marked by radiologists into two-classes (COVID-19 and non-COVID-19). We address the class imbalance problem associated with the training dataset by proposing a novel transfer-to-transfer learning approach, where we break a highly imbalanced training dataset into a group of balanced mini-sets and …

Pedagogy Of The Pandemic: A Case Study Of Emergency Remote Education In A Private Higher Education Institution In Egypt, Rania M Rafik Khalil, Shadia Fahim, Wadouda Badran, Hadia Fakhreldin, Maguid Hassan, Hani Ghali, Attia Attia, Sarah Khalil, Hassan Abdelhamid, Yasmine Abdel Moneim, Omar H. Karam

English Language and Literature

COVID19 caught almost every higher education institution off guard. The pandemic interrupted the teaching and learning process and required immediate implementation of emergency remote learning strategies. Teaching pedagogy turned to new ways of thinking about learning. Consequently, both academic staff and students had to adapt without warning to the challenges of teaching with advanced technology from home which was taking the world by storm. Overcoming this challenge in Egypt has been much easier for private universities in comparison to state universities because of the availability of facilities, funding, smaller cohorts and validation by partner western universities. This paper shares reflections …

Bibliometric Analysis Of Firefly Algorithm Applications In The Field Of Wireless Sensor Networks, Anupkumar M. Bongale Dr., Rahul Raghvendra Joshi Prof., Kalyani Dhananjay Kadam Prof.

Library Philosophy and Practice (e-journal)

Wireless Sensor Network is a network of wireless sensor nodes that are capable of sensing information from their surroundings and transmit the sensed information to data collection point known as a base station. Applications of wireless sensor networks are large in number and forest fire detection, landslide monitoring, etc. are few applications to note. The research challenges in wireless sensor networks is the transmission of data from the sensor node to the base station in an energy-efficient manner and network life prolongation. Cluster-based routing techniques are extensively adopted to address this research challenge. Researchers have used different metaheuristic and soft …

A Systematic Literature Review With Bibliometric Meta-Analysis Of Deep Learning And 3d Reconstruction Methods In Image Based Food Volume Estimation Using Scopus, Web Of Science And Ieee Database, Prachi Kadam, Nayana Petkar, Shraddha Phansalkar Dr.

Library Philosophy and Practice (e-journal)

Purpose- Estimation of food portions is necessary in image based dietary monitoring techniques. The purpose of this systematic survey is to identify peer reviewed literature in image-based food volume estimation methods in Scopus, Web of Science and IEEE database. It further analyzes bibliometric survey of image-based food volume estimation methods with 3D reconstruction and deep learning techniques.

Design/methodology/approach- Scopus, Web of Science and IEEE citation databases are used to gather the data. Using advanced keyword search and PRISMA approach, relevant papers were extracted, selected and analyzed. The bibliographic data of the articles published in the journals over the past …

The Effect Of Information Technology Audit For E-Health Of Indonesia Using Itil Framework V.3 Domain Service Design, Eva Mufidah, Ilham M, Anis Eliyana, Tanti Handriana, Indrianawati Usman

Library Philosophy and Practice (e-journal)

This study explain about E-Health Surabaya is a web-based health service technology application that is used to help people register as patients in hospitals and health centers. Although its function is very useful, there are also people who still do not understand how to use this application, there are also some shortcomings that cause inconvenience in its use. So that research is conducted in which the application uses ITIL V.3 framework with Domain Service Design to conduct an audit of the maturity level of this E-Health Surabaya Web Application. ITIL (Information Technology Infrastructure Technology) is a framework used to manage …

Demystifying Artificial Intelligence Based Digital Twins In Manufacturing- A Bibliometric Analysis Of Trends And Techniques, Satish Kumar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Anup Kumar M. Bongale, Pooja Kamat

Library Philosophy and Practice (e-journal)

Nowadays, data is considered as a new life force for operations of physical systems in various domains such as manufacturing, healthcare, transportations, etc. However, the hugely generated data, which mirrors the working essence of the product life cycle, is still underutilised. Digital Twin (DT), a collective representation of active and passive captured data, is a virtual counterpart of the physical resources that could help prevent effective preventive maintenance in any applied domain. Currently, lots of research is going on about the applicability of digital twin in smart IOT based manufacturing industry 4.0 environment. Still, it lacks a formal study, which …

A Real-Time And Adaptive-Learning Malware Detection Method Based On Api-Pair Graph, Shaojie Yang, Shanxi Li, Wenbo Chen, Yuhong Liu

Computer Science and Engineering

The detection of malware have developed for many years, and the appearance of new machine learning and deep learning techniques have improved the effect of detectors. However, most of current researches have focused on the general features of malware and ignored the development of the malware themselves, so that the features could be useless with the time passed as well as the advance of malware techniques. Besides, the detection methods based on machine learning are mainly static detection and analysis, while the study of real-time detection of malware is relatively rare. In this article, we proposed a new model that …

Digital And Mixed Domain Hardware Reduction Algorithms And Implementations For Massive Mimo, Najath A. Mohomed

FIU Electronic Theses and Dissertations

Emerging 5G and 6G based wireless communications systems largely rely on multiple-input-multiple-output (MIMO) systems to reduce inherently extensive path losses, facilitate high data rates, and high spatial diversity. Massive MIMO systems used in mmWave and sub-THz applications consists of hundreds perhaps thousands of antenna elements at base stations. Digital beamforming techniques provide the highest flexibility and better degrees of freedom for phased antenna arrays as compared to its analog and hybrid alternatives but has the highest hardware complexity.

Conventional digital beamformers at the receiver require a dedicated analog to digital converter (ADC) for every antenna element, leading to ADCs for …

Geographic Data Mining And Knowledge Discovery, Liangdong Deng

FIU Electronic Theses and Dissertations

Geographic data are information associated with a location on the surface of the Earth. They comprise spatial attributes (latitude, longitude, and altitude) and non-spatial attributes (facts related to a location). Traditionally, Physical Geography datasets were considered to be more valuable, thus attracted most research interest. But with the advancements in remote sensing technologies and widespread use of GPS enabled cellphones and IoT (Internet of Things) devices, recent years witnessed explosive growth in the amount of available Human Geography datasets. However, methods and tools that are capable of analyzing and modeling these datasets are very limited. This is because Human Geography …

A Structural Equation Model Analysis Of Computing Identity Sub-Constructs And Student Academic Persistence, Mohsen Taheri

FIU Electronic Theses and Dissertations

This dissertation explores the impact of computing identity sub-constructs on the academic persistence of computing students. This research provides models, quantified relationships, and insights to increase the number of graduates with the intention of pursuing a career in computing. Despite the growing significance of computer science and all the projected new jobs in computer science, many university and college programs suffer from low student persistence rates. One theoretical framework used to better understand persistence in other STEM disciplines is disciplinary identity. Disciplinary identity refers to how students see themselves with respect to a discipline. This study examines the effects of …

Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, Alexis Papamichail, Vanya Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

Strain-stress relationships for physical properties are of interest for heteroepitaxial material systems, where strain and stress are inherent due to thermal expansion and lattice mismatch. We report linear perturbation theory strain and stress relationships for optical phonon modes in monoclinic crystals for strain and stress situations which maintain the monoclinic symmetry of the crystal. By using symmetry group analysis and phonon frequencies obtained under various deformation scenarios from density-functional perturbation theory calculations on β-Ga₂O₃, we obtain four strain and four stress potential parameters for each phonon mode. We demonstrate that these parameters are sufficient to …

Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, A. Papamichail, V. Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

Strain-stress relationships for physical properties are of interest for heteroepitaxial material systems, where strain and stress are inherent due to thermal expansion and lattice mismatch. We report linear perturbation theory strain and stress relationships for optical phonon modes in monoclinic crystals for strain and stress situations which maintain the monoclinic symmetry of the crystal. By using symmetry group analysis and phonon frequencies obtained under various deformation scenarios from density-functional perturbation theory calculations on β-Ga₂O₃, we obtain four strain and four stress potential parameters for each phonon mode. We demonstrate that these parameters are sufficient to …